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Stroke

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Task-Oriented Training by a Personalized Electromyography-Driven Soft Robotic Hand in Chronic Stroke: A Randomized Controlled Trial.

Neurorehabilitation and neural repair
BACKGROUND: Intensive task-oriented training has shown promise in enhancing distal motor function among patients with chronic stroke. A personalized electromyography (EMG)-driven soft robotic hand was developed to assist task-oriented object-manipula...

Mitigating Trunk Compensatory Movements in Post-Stroke Survivors through Visual Feedback during Robotic-Assisted Arm Reaching Exercises.

Sensors (Basel, Switzerland)
Trunk compensatory movements frequently manifest during robotic-assisted arm reaching exercises for upper limb rehabilitation following a stroke, potentially impeding functional recovery. These aberrant movements are prevalent among stroke survivors ...

Deep learning of left atrial structure and function provides link to atrial fibrillation risk.

Nature communications
Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to asse...

Predictive modelling and identification of key risk factors for stroke using machine learning.

Scientific reports
Strokes are a leading global cause of mortality, underscoring the need for early detection and prevention strategies. However, addressing hidden risk factors and achieving accurate prediction become particularly challenging in the presence of imbalan...

The independence of impairments in proprioception and visuomotor adaptation after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Proprioceptive impairments are common after stroke and are associated with worse motor recovery and poor rehabilitation outcomes. Motor learning may also be an important factor in motor recovery, and some evidence in healthy adults sugges...

Effects of Rehabilitation Robot Training on Physical Function, Functional Recovery, and Daily Living Activities in Patients with Sub-Acute Stroke.

Medicina (Kaunas, Lithuania)
Stroke often results in sensory deficits, muscular weakness, and diminished postural control, thereby restricting mobility and functional capabilities. It is important to promote neuroplasticity by implementing task-oriented exercises that induce cha...

Effects of robot-assisted gait training using the Welwalk on gait independence for individuals with hemiparetic stroke: an assessor-blinded, multicenter randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Gait disorder remains a major challenge for individuals with stroke, affecting their quality of life and increasing the risk of secondary complications. Robot-assisted gait training (RAGT) has emerged as a promising approach for improving...

Effect of task-oriented training assisted by force feedback hand rehabilitation robot on finger grasping function in stroke patients with hemiplegia: a randomised controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Over 80% of patients with stroke experience finger grasping dysfunction, affecting independence in activities of daily living and quality of life. In routine training, task-oriented training is usually used for functional hand training, w...

Developing machine learning models to predict multi-class functional outcomes and death three months after stroke in Sweden.

PloS one
Globally, stroke is the third-leading cause of mortality and disability combined, and one of the costliest diseases in society. More accurate predictions of stroke outcomes can guide healthcare organizations in allocating appropriate resources to imp...

Voxel level dense prediction of acute stroke territory in DWI using deep learning segmentation models and image enhancement strategies.

Japanese journal of radiology
PURPOSE: To build a stroke territory classifier model in DWI by designing the problem as a multiclass segmentation task by defining each stroke territory as distinct segmentation targets and leveraging the guidance of voxel wise dense predictions.